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Web-Based Music Synthesizer

Data Analyst Project completed by Joseph Wankelman

HTML | CSS | JavaScript | Bootstrap Framework | OOP | Tone.js | Web Components | Speech Synthesis API | JavaScript Event Handling | Data Manipulation and Visualizations | Version Control (Git)

Project Description

This project showcases my ability to build an interactive, web-based music synthesizer using a combination of HTML, CSS, and JavaScript. Through this project, I leveraged data-driven decision-making to optimize the user interface and incorporated complex sound synthesis algorithms to provide users with an immersive auditory experience. The synthesizer features a dynamic visualizer and speech synthesis components, allowing users to manipulate audio parameters such as pitch, frequency, volume, and tempo. In building this project, I not only demonstrated technical skills but also utilized strategic economic principles to enhance user engagement and retention through a user-friendly interface and streamlined performance optimization.

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The development process involved applying economic theories of supply and demand to determine which features would provide the most value to users without overcomplicating the interface, ensuring efficient code execution and minimizing server load. Additionally, the integration of business skills such as market analysis and consumer behavior insights allowed for the creation of a product that meets both artistic and market needs, enhancing the synthesizer's appeal to a broad audience.

Project Skills

ArcGIS Web Development: Utilized ArcGIS to develop a sophisticated, interactive website that allows campaign teams to explore voter precinct data visually, offering an intuitive platform for understanding voter behaviors across the region.

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Statistical and Predictive Analysis: Employed statistical tools and methods such as regression analysis, clustering, and spatial analytics to evaluate voter turnout, demographics, and voting trends. These insights guide where campaign resources, such as signage and canvassing, should be focused.

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Data Science Methodologies: Implemented machine learning models, including neural networks and decision trees, to predict voter engagement, identify key precincts, and forecast voter behavior, providing campaigns with actionable intelligence.

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Psychographic and Behavioral Analytics: Merged voter data with psychographic and behavioral indicators, giving campaigns an in-depth understanding of voter motivations and preferences. This enabled targeted outreach strategies tailored to specific demographic segments.

Project Demostrates

The synthesizer project exemplifies my web development mastery by integrating advanced audio and visual elements for a smooth user experience across devices. It demonstrates my strategic business insight through the alignment of technical features with market demand, optimizing both performance and cost efficiency. Additionally, the project highlights my human capital, showcasing my ability to transform complex technical challenges into marketable solutions, underscoring the value I bring in development and strategic business planning.

© 2024 by Joseph Wankelman and secured by Wix

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